A new paper argues against the immediate automation of academic peer review using current large language models. The research highlights two major issues: AI reviewers exhibit an excessive agreement, limiting diverse perspectives, and their scores can be easily manipulated through stylistic paper rewrites rather than genuine scientific merit. The authors propose that a dedicated science of peer review automation is necessary, rather than deploying general-purpose LLMs without thorough evaluation. AI
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IMPACT Current LLMs are not suitable for automating peer review due to lack of diversity and susceptibility to manipulation, necessitating specialized research.
RANK_REASON Academic paper evaluating the use of LLMs in peer review. [lever_c_demoted from research: ic=1 ai=1.0]